
\begin{table}
\begin{center}
\begin{tabular}{l D{)}{)}{9)2} D{)}{)}{9)0} D{)}{)}{9)2} D{)}{)}{9)0} D{)}{)}{9)1}}
\toprule
 & \multicolumn{1}{c}{Care} & \multicolumn{1}{c}{Fairness} & \multicolumn{1}{c}{Loyalty} & \multicolumn{1}{c}{Authority} & \multicolumn{1}{c}{Sanctity} \\
\midrule
GAL-TAN (CHES)           & 0.01 \; (0.16)       & 0.12 \; (0.17)  & 0.25 \; (0.15)      & 0.10 \; (0.17)  & -0.09 \; (0.17)     \\
Year                     & -0.01 \; (0.15)      & -0.06 \; (0.16) & -0.13 \; (0.14)     & -0.21 \; (0.16) & 0.06 \; (0.17)      \\
Government Participation & -0.91 \; (0.29)^{**} & 0.08 \; (0.32)  & 0.76 \; (0.26)^{**} & 0.28 \; (0.31)  & -0.75 \; (0.33)^{*} \\
\midrule
AIC                      & 104.53               & 110.24          & 103.09              & 109.32          & 110.66              \\
BIC                      & 113.87               & 119.57          & 112.42              & 118.66          & 119.99              \\
Log Likelihood           & -46.27               & -49.12          & -45.54              & -48.66          & -49.33              \\
Num. manifestos          & 35                   & 35              & 35                  & 35              & 35                  \\
Num. groups: countries   & 4                    & 4               & 4                   & 4               & 4                   \\
Var: Country (Intercept) & 0.36                 & 0.37            & 2.09                & 0.52            & 0.00                \\
Var: Residual            & 0.68                 & 0.83            & 0.56                & 0.79            & 0.94                \\
\bottomrule
\multicolumn{6}{l}{\scriptsize{$^{***}p<0.001$; $^{**}p<0.01$; $^{*}p<0.05$}}
\end{tabular}
\caption{Regression table for all manifestos in German, scored with CCR (engl ref, multi embed) for the dimension Virtue.}
\label{tab:app_reg_de_ccr_multi_to_en_virtue}
\end{center}
\end{table}
